xAI· Infrastructure· Memphis, TN; Palo Alto, CA
Network Engineer - AI/HPC
Classified Tasks (23)
Automate 0%Augment 78%Human-Only 22%
Augment (18)
AI assists, human decides
Develop RoCEv2-based network systems at hyper scale.
technical
Optimize network performance and availability for AI training workloads.
technical
Optimize network performance and availability for customer inference queries.
technical
Analyze current network performance and availability to identify bottlenecks.
analytical
Debug, instrument, and modify NCCL to improve communication performance.
technical
Build and maintain metric dashboards for performance and operational visibility.
operational
Tweak network and NCCL configurations to maximize throughput and minimize latency.
technical
Implement automation to enable seamless GPU infrastructure build-outs with minimal engineering assistance.
operational
Perform scaling activities to grow cluster and network capacity.
operational
Develop deployment and operations frameworks to remove repetitive manual tasks.
operational
Write Python scripts to automate repetitive tasks and data-processing workflows.
technical
Analyze large datasets to inform network tuning and operational decisions.
analytical
Create and maintain a portfolio of performance and operations metrics for fleet optimization.
analytical
Profile AI training and inference traffic patterns and adapt network configurations accordingly.
analytical
Benchmark, profile, and tune congestion-control behavior on ethernet (and Infiniband where applicable).
technical
Monitor fleet-wide performance and availability and implement corrective actions.
operational
Contribute code changes and commits to NCCL or related libraries.
technical
Collaborate with engineers to instrument and collect large-scale network telemetry.
technical
Human-Only (5)
Requires human judgment
Design next-generation backend network architectures to support scalable GPU deployments.
technical
Design next-generation front-end network architectures to support scalable GPU deployments.
technical
Travel to Memphis to deploy and expand GPU and network capacity.
operational
Participate in on-call rotation to troubleshoot and resolve production incidents.
operational
Perform maintenance activities on network and GPU infrastructure.
operational
Job description
ABOUT xAI xAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. ABOUT THE ROLE: xAI was first in the world to build a 100k GPU cluster on an ethernet network and then did it again in 92 days, floors, walls and all. We need an engineer with deep experience in RoCEv2 that can develop at hyper scale while optimizing performance and availability. xAI is building at a furious pace with the latest hardware to help people understand the universe. To make the next significant leap forward, we need to own our own destiny by understanding our current network performance and availability and then optimize it to our training models and how we execute customer inference queries. You will spend most of your days deep inside NCCL, building metric dashboards and tweaking configurations to ensure no performance is left on the table. You will help design the next iteration of our backend and front-end networks that will allow us to seamlessly build-out new GPU infrastructure with little to no engineering assistance. There will be a significant amount of travel to Memphis for building more capacity as well as participating in a team on-call rotation and helping on other scaling and maintenance efforts. This will become easier as we build out the team and engineers contribute to deployment and operations frameworks to remove repetitive tasks. BASIC QUALIFICATIONS: A minimum of 10 years designing and operating large scale networks with 5 years in the ethernet AI/HPC space. Deep understanding of congestion control on ethernet with Infiniband an added bonus. Deep understanding of AI training and inference workloads and how they operate on the network. As part of this you are able to use and debug NCCL and potentially commit to the library. Expertise in creating a portfolio of metrics for performance and operations to optimize the fleet for training and inference traffic. Experience with Python to automate away repetitive tasks and facilitate your daily job working with and analyzing large sets of data. xAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice .